a28_2_korean.py

#%%

from import_all import *

from selenium import webdriver
from PIL import Image
# import pytesseract
#%%
# Setup WebDriver (make sure chromedriver is in your PATH)
driver = open_driver_loop()
#%%

# mongo_collection_names('stock')
#%%
# ticker='AAPL'
# dt=mongo_get_df('stock','comparison')
# dt
#%%
# tickers=dt['ticker'].values.tolist()
tickers2=kosdaq_mc_list_500(80)
tickers=kospi_mc_list_500(80)
tickers.extend(tickers2)
#%%
currency='$'
currency='KRW'
def run(ticker):

    print("ticker: ",ticker)
    # exchange=find_exchange_v2(ticker)
    exchange="KRX"
    driver.get(f'https://www.tradingview.com/chart/q0QCLsTJ/?symbol={exchange}%3A{ticker}')  # URL where the canvas is located
    time.sleep(10)


    button=driver.find_element(By.XPATH,'//button[@class="button-vll9ujXF button-KSzJG6_A"]')

    if 'dropped' in button.find_element(By.TAG_NAME,'span').get_attribute('class'):
        print('down now')
    else:
        button.click()
        print('up now')
    time.sleep(1)
    titles=driver.find_elements(By.XPATH,'//span[@class="title-cXDWtdxq itemTitle-KSzJG6_A"]')
    infos=driver.find_elements(By.XPATH,'//span[@class="data-cXDWtdxq"]')

    dict1={}
    dict1['ticker']=ticker
    for title,item in zip(titles,infos):
        title=title.text
        item=item.text
        if item.endswith('B'):
            item=item.replace('B','')
            item=float(item)
            item=item*1000000
        elif item.endswith('M'):
            item=item.replace('M','')
            item=float(item)
            item=item*1000
        elif item.endswith('T'):
            item=item.replace('T','')
            item=float(item)
            item=item*1000000000
        elif item.endswith('K'):
            item=item.replace('K','')
            item=float(item)
            
        elif item.endswith('%'):
            item=item.replace('%','')
            item=float(item)
        
        else:
            try:
                item=float(item)
            except:
                item=float(0)
        dict1[title]=item
        
        print("item: ",title,item)
    dict1




    dd=pd.DataFrame.from_dict(dict1,orient='index').T
    dd

    
    # Locate the canvas element
    canvas = driver.find_elements(By.TAG_NAME,'canvas')
    canvas
    canvase=driver.find_elements(By.XPATH,'//canvas[@aria-hidden="true"]')

    pt.moveTo(60,200)
    time.sleep(1)
    canvas=canvase[5]

    # Get the location and size of the canvas element
    location = canvas.location
    size = canvas.size

    # Take a screenshot of the entire page
    driver.save_screenshot('data/page_image.png')

    # Open the screenshot and crop it to the canvas area
    # x, y = location['x'], location['y']+500

    row=[]
    row.append(ticker)



    list1=[(56,404),(56,404+365),(56,404+365*2),(56,404+365*3),(56,404+365*4),(56,404+365*5)]
    i=0
    for i in range(len(list1)):
        x,y=list1[i]

        # x, y = location['x'], location['y']

        # width, height = size['width'], size['height']
        width=2692
        height=228
        image = Image.open('data/page_image.png')
        canvas_image = image.crop((x+350, y-130, x + width+1650, y + height+20))
        # canvas_image = image.crop((x, y, x + width+1400, y + height+120))
        canvas_image.save('data/canvas_image.png')
        # canvas_image.show()

        size


        # Clean up
        




        # def detect_text(path):

        """Detects text in the file."""
        path='data/canvas_image.png'
        total_text=image2text(path)


        total_text=total_text.split('\n')
        print("total_text: ",total_text)
        
        
        try:
            numbers=[]
            for text in total_text:
                # text=item.description
                print("text: ",text)
                # print(f'\n"{item.description}"')
                if text.startswith(currency) and text:
                    print("text: ",text)
                    # found_numbers = re.findall(r'\d+\.\d+', text)
                    found_numbers = re.findall(r'-?\d+\.\d+', text)
                    print("found_numbers: ",found_numbers)
                    if found_numbers == '' or found_numbers==None or len(found_numbers)==0:
                        found_numbers='0'
                    if text.endswith('B'):
                        found_numbers=float(found_numbers[0])*1000000
                    elif text.endswith('M'):
                        found_numbers=float(found_numbers[0])*1000
                    numbers.append(found_numbers)
            numbers
        except:
            numbers=[]
            define='''reformat each element so that the list looks like "['$10.516B', '$7.796B', '$9.014B', '$17.891B',...]"'''
            for _ in range(3):
                try:
                    print('''> try: summary=gpt_answer_v2(str(total_text),define)''',datetime.now())
                    summary=gpt_answer_v2(str(total_text),define)
                    
                    summary
                    list2=ast.literal_eval(summary)
                    list2
                    for text in list2:
                        # found_numbers = re.findall(r'\d+\.\d+', text)
                        found_numbers = re.findall(r'-?\d+\.\d+', text)

                        if found_numbers == '' or found_numbers==None or len(found_numbers)==0:
                            found_numbers='0'
                        print("found_numbers: ",found_numbers)
                        if text.endswith('B'):
                            
                            found_numbers=float(found_numbers[0])*1000000
                        elif text.endswith('M'):
                            found_numbers=float(found_numbers[0])*1000
                        numbers.append(found_numbers)
                    break
                except Exception as e:
                    time.sleep(1)
                    print('''>> error: summary=gpt_answer_v2(str(total_text),define): ''',e,datetime.now())

        row.append(str(numbers))

    row[1:] 

    slopes1=[]
    slopes1.append(ticker)
    for numbers in row[1:]:
        numbers=ast.literal_eval(numbers)
        # numbers=[float(item[0]) for item in numbers if isinstance(item, list) elif isinstance(obj, float) item]
        
        
        try:
            print('''> try: slope1,intercept=regression(numbers)''',datetime.now())
            numbers = [float(item[0]) if isinstance(item, list) else float(item) for item in numbers]
            slope1,intercept=regression(numbers,normalize=True)
        except Exception as e:
            slope1=0
            print('''>> error: slope1,intercept=regression(numbers): ''',e,datetime.now())

        slope1=slope1*1000
        slope1=round(slope1,2)
        slopes1.append(slope1)
        slopes1.append(str(numbers))
    for numbers in row[1:]:
        numbers=ast.literal_eval(numbers)
        try:
            numbers = [float(item[0]) if isinstance(item, list) else float(item) for item in numbers]
            print('''> try: slope1,intercept=regression(numbers[-8:])''',datetime.now())
            slope1,intercept=regression(numbers[-8:],normalize=True)
        except Exception as e:
            print('''>> error: slope1,intercept=regression(numbers[-8:]): ''',e,datetime.now())
            slope1=0
        slope1=slope1*1000
        slope1=round(slope1,2)
        slopes1.append(slope1)
    slopes1
    print("slopes1: ",slopes1) 

    numbers=row[1]
    numbers=ast.literal_eval(numbers)
    numbers

    dn=pd.DataFrame(slopes1).T
    dn#%

    dn.columns=['ticker','revenue1','revenue','gross_profit1','gross_profit','net_income1','net_income','dividend1','dividend','fcf1','fcf','cogs1','cogs','revenue2','gross_profit2','net_income2','dividend2','fcf2,','cogs2']
    print("dn: ",dn)

    dn=dd.merge(dn,how='outer',on='ticker')

    # mongo_insert(dn,'ticker','stock','korean_slope')
    mongo_update_insert_one('stock','korean_slope',dn,'ticker')
#%%
ds=mongo_get_df('stock','korean_slope')
ds


#%%
ds[['revenue1','revenue','gross_profit1','gross_profit','net_income1']]
#%%
tickers2=[]
for a,b,c in tickers:
    if 'TIGER' in a or '레버리지' in a or '스팩' in a or 'KODEX' in a or 'S&P' in a or 'ACE' in a or 'ESG' in a or 'ETN' in a or '인버스' in a or 'SOL' in a or 'KBSTAR' in a or 'KOSEF' in a or 'QV' in a or 'ARIRANG' in a:
        pass
    else:
        tickers2.append(b)

#%%
        

# tickers=[b for a,b,c in tickers]
tickers=tickers2

target_column='ticker'
total_list=tickers
undone_items=[]
do_list=ds[target_column].values.tolist()
undone_items=list_minus(total_list,do_list)
print("\n>> len(undone_items)= ", len(undone_items))
print("\n>> len(total_list)= ", len(total_list))


#%%
undone_items
#%%
for ticker in undone_items:
    if 1600<int(datetime.strftime(datetime.now(timezone('US/Eastern')) ,"%H%M"))<2000 :
        pass
    else:
        try:
            print('''> try: run(ticker)''',datetime.now())
            run(ticker)
        except Exception as e:
            time.sleep(30)
            print('''>> error: run(ticker): ''',e,datetime.now())

# for ticker in undone_items:
#     if 1600<int(datetime.strftime(datetime.now(timezone('US/Eastern')) ,"%H%M"))<2000 :
#         pass
#     else:
#         run(ticker)
# %%
# mongo_set_df('stock','korean_slope','ticker',dn)
#%%
#%%
print("\n>> len(tickers)= ", len(tickers))

# %%

ds=mongo_get_df('stock','korean_slope')
ds

# %%


ds2=ds[['ticker','revenue1','revenue2','net_income1','net_income2']]
ds2 = ds2[ds2['revenue1'] >= 30]
ds2 = ds2[ds2['revenue2'] >= 30]
ds2 = ds2[ds2['net_income1'] >= 30]
ds2 = ds2[ds2['net_income2'] >= 30]
ds2=ds2.sort_values(by='revenue2',ascending=False)
ds2[:20]
# %%
ticker='AAPL'
endpoint=f'https://api.polygon.io/v3/reference/tickers/{ticker}?apiKey={polygon_api_key}'
response = requests.get(endpoint)
# Raise an error if the request failed
response.raise_for_status()
# Parse the JSON result
data = response.json()

json_data=data['results']

new_row = pd.DataFrame(json_data, index=[0])
new_row['primary_exchange']
# %%
new_row.columns
# %%
find_exchange_v2('AIRI')
# %%